Enhancing Mobility in Smart Cities: People Counting and Characteristics Detection in Public Buses
Amirgaliyev B. Mussabek M. Zhumadillayeva A. Baishemirov Z.
2025Institute of Electrical and Electronics Engineers Inc.
IEEE European Technology and Engineering Management Summit, E-TEMS
2025Issue 2025264 - 269 pp.
Detecting passengers and tracking them in public transport is a crucial task in the reality of Smart City(SC) environment. This task combines with additional calculations like passenger counting and utilizes technologies in Computer Vision(CV) field. We explore and evaluate FairMOT hybrid model for passenger counting. It is a state-of-the-art multi-object tracking system that integrates detection and Re-Identification(re-ID) within a single network. This model was trained on 180 videos with a total of 70,710 frames of open source videos containing passenger flow in public buses. Evaluation on different videos showed maximum Recall(97.9%) and MOTA(82.5%) scores. Also moderate IDF1(73.6%) scores. It shows great tracking accuracy and introduces a computationally efficient framework, offering transit operators a scalable and effective solution to optimize passenger flow analysis in SC environment.
deep learning , passenger counting , person re-identification , person tracking
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Astana IT University, Department of Computer Engineering, Astana, Kazakhstan
KBTU, Department of Mathematics and Mathematical Modeling, Almaty, Kazakhstan
Astana IT University
KBTU
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026